ObjectiveProtein-protein interactions (PPIs) are fundamental to the execution of biological functions within living cells. However, traditional biochemical methods, such as co-immunoprecipitation (Co-IP), often fail to capture transient, weak, or membrane-associated interactions due to the stringent detergent requirements for cell lysis. Proximity labeling (PL) has emerged in recent years as a transformative technology for mapping the proteomes of specific subcellular compartments and identifying dynamic interactomes in situ. Golgi protein 73 (GP73, also known as GOLPH2), a resident type II Golgi transmembrane protein, is a well-recognized clinical biomarker for liver diseases, including hepatocellular carcinoma (HCC). Despite its clinical significance, the comprehensive physiological and pathological functions of GP73 remain partially understood. This study aims to establish an APEX2-mediated proximity labeling system specifically targeting GP73 to map its interactome in a living cellular environment, thereby providing new insights into its molecular roles and regulatory mechanisms. MethodsTo achieve spatial specificity, we first constructed a stable cell line expressing a fusion protein consisting of GP73 and the engineered soybean peroxidase APEX2. The localization of the GP73-APEX2 fusion protein was validated to ensure it correctly targeted the Golgi apparatus. The proximity labeling reaction was initiated by incubating the cells with biotin-phenol (BP) for 30 min, followed by a brief (1 min) treatment with1 mmol/L hydrogen peroxide (H₂O₂). This catalytic reaction converts BP into highly reactive, short-lived biotin-phenoxyl radicals that covalently attach to endogenous proteins within a small labeling radius of the GP73-APEX2 enzyme. Subsequently, the cells were quenched, and biotinylated proteins were enriched using high-affinity streptavidin-coated magnetic beads. The captured “neighbor” proteins were subjected to on-bead digestion and analyzed via liquid chromatography-tandem mass spectrometry (LC-MS/MS) for high-throughput identification. Rigorous bioinformatics analysis, including Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein-protein interaction network mapping, was performed to interpret the biological significance of the identified candidates. ResultsOur results demonstrate the successful establishment of a robust and sensitive APEX2-based proximity labeling system for GP73. We identified a total of 95 high-confidence interacting proteins that were significantly enriched in the GP73 proximity proteome compared to control groups. Bioinformatics analysis revealed that these interactors were predominantly associated with biological processes such as vesicular transport, protein localization, and, most notably, molecular functions related to “ribosome binding” and “translation regulation”. This suggested an unexpected role for the Golgi-resident GP73 in the cellular translation machinery. To validate these findings, we performed targeted biochemical assays which confirmed a direct interaction between GP73 and the subunits of the eukaryotic translation initiation factor 3 (eIF3) complex, specifically EIF3G and EIF3I. Furthermore, functional validation using the surface sensing of translation (SUnSET) assay—a non-radioactive method to monitor protein synthesis—revealed that the overexpression of GP73 significantly promoted global protein translation levels in the cell, whereas its depletion or inhibition resulted in reduced translation efficiency. ConclusionThis study successfully utilized APEX2-mediated proximity labeling to provide the first systematic map of GP73 interactome in living cells. Our findings uncover a novel, unconventional function of GP73 as a regulator of cellular protein translation, likely mediated through its interaction with the eIF3 complex. This discovery significantly broadens our understanding of the biological roles of GP73 beyond its traditional function in the Golgi apparatus and suggests that it may act as a bridge between Golgi-related trafficking and the protein synthesis machinery. Furthermore, the technical framework established in this study provides a valuable template for investigating other complex organelle-associated protein networks and resolving transient macromolecular interactions in various physiological and pathological contexts.

Objective: To understand the microclimate in primary and secondary school classrooms for the study period during the winter heating season, so as to provide a reference for the revision and improvement of relevant health standards. Methods: In December 2024, stratified random sampling was used to select 30 primary and secondary schools and 180 classrooms from the northern regions with centralized heating (Liaoning Province, Tianjin City) and the southern regions without centralized heating (Shanghai City, Anhui Province, and Jiangxi Province). Indoor temperature, relative humidity, wind speed, CO 2 and other indicators were measured on site. Variance analysis, t-test, Mann-Whitney U test and Kruskal-Wallis H test were used to analyze the differences in the microclimate of classrooms among regions and urban and rural differences. Results: The average temperature in the middle of the classrooms tested on site was (16.47±4.72)℃, and the variance analysis showed that the difference between the regions was statistically significant ( F=27.80, P <0.01). Among them, Tianjin had the highest average temperature of (20.43± 2.12 )℃, followed by Liaoning (19.03±2.23)℃, Shanghai (15.33±5.32)℃, Anhui (12.79±1.74)℃, and Jiangxi (11.69± 1.68 )℃. Horizontal temperature difference was 0.90 (0.50, 1.60)℃, the vertical temperature difference was 0.20 (0.10,0.60)℃, the average relative humidity was (44.39±16.16)%, the wind speed was 0.03(0.01,0.11)m/s, and the differences among different provinces and cities were statistically significant ( H/F =40.62, 82.69, 95.06, 55.28, all P <0.01). The average CO 2 volume concentration in urban areas of Tianjin, Liaoning, and Shanghai was 0.21(0.16,0.30)%, and there was no statistically significant difference ( H=4.65, P =0.10). There were grade differences in relative humidity ( F =3.71, 6.21) and CO 2 ( H =14.72, 12.92) in the north and the south (all P <0.05). In addition, the temperature, relative humidity, wind speed and CO 2 in the middle of the classroom were 42.8%, 67.8%, 100.0% and 22.2% respectively. Conclusions The temperature in the middle of the classroom in the non centralized heating area is lower than the standard, the relative humidity of classroom in the centralized heating area is lower than the standard，and the CO 2 in the classroom in winter is lower than the standard. It is recommended to install heating facilities in schools with low temperatures to increase the temperature and increase the frequency of ventilation in classrooms or adopt mechanical ventilation strategies to reduce CO 2 volume concentration.

Objective:To observe the effect of hyperthermia combined with iron overload on the regulation of tumor-associated macrophage polarization and the migration ability of CAL-27 cells and explore its mechanism.Methods:Human monocytic leukemia cell THP-1 was induced and polarized into M2 macrophages. M2 tumor-associated macrophages and CAL-27 cells were divided into the control group (no intervention), hyperthermia group (incubated at 42 ℃ for 1 h, and then incubated at 37 ℃ for 24 h), ferric citrate group (added with 2.5 mg/ml ferric citrate, and cultured in an incubator at 37 ℃for 24 h) and hyperthermia + ferric citrate group (added with 2.5 mg/ml ferric citrate for 1 h, cultured in an incubator at 42℃ for 1 h, and then incubated at 37℃ for 24 h). For M2 macrophage groups, the mRNA relative expression levels of surface markers of M1 macrophage polarization including interleukin (IL)-1β, tumor necrosis factor-α(TNF-α), and those of M2 macrophage polarization including IL-10 and transforming growth factor-β(TGF-β) were detected by real-time reverse transcription polymerase chain reaction. The expression levels of IL-1β and IL-10 were detected by ELISA. The expression levels of CD86 (surface marker of M1 macrophage polarization) and CD206 (surface marker of M2 macrophage polarization) were measured by flow cytometry. The expression levels of signal transducer and activator of transcription 3 (STAT3), Toll-like receptor 4 (TLR4), nuclear factor κB (NF-κB) and phosphorylated (p)-NF-κB were detected by Western blot (WB). The migration ability of CAL-27 cells was assessed by scratch assay.Results:Compared with the control group, the expression levels of IL-1βand TNF-α mRNA, and IL-1βand CD86 proteins were up-regulated, whereas those of IL-10 and TGF-β mRNA, and IL-10 and CD206 proteins were down-regulated in the hyperthermia, ferric citrate and hyperthermia + ferric citrate groups, respectively (all P<0.05). In addition, the changes in the hyperthermia+ferric citrate group were significantly larger than those in the hyperthermia and ferric citrate groups (all P<0.05). WB showed that the expression level of STAT3 protein was down-regulated and those of TLR4, NF-κB and p-NF-κB expression were up-regulated in the hyperthermia + ferric citrate group (all P<0.05). Scratch assay showed that the migration ability of CAL-27 cells was inhibited in the hyperthermia, ferric citrate and hyperthermia + ferric citrate groups ( P<0.001), and the changes in the hyperthermia + ferric citrate group were significantly more pronounced than those in the hyperthermia and ferric citrate groups (both P<0.001). Conclusions:Hyperthermia and iron overload can promote the polarization of M1 macrophages and inhibit the polarization of M1 macrophages into M2 macrophages, thereby suppressing the migration of oral squamous cell carcinoma. The mechanism may be related to inhibiting the expression of STAT3 and activating the TLR4/NF-κB signaling pathway.

Objective To investigate the correlation between hemoglobin A1c(HbA1c)levels and excessive daytime sleepiness(EDS)in patients with type 2 diabetes mellitus(T2DM).Methods A total of 132 T2DM patients and 40 healthy people(NC group)who were treated in the outpatient department of Nanjing Meishan Hospital from December 2020 to December 2022 were selected.General clinical data of the subjects were collected,and their Epworth sleepiness scale(ESS)scores,Pittsburgh sleep quality index(PSQI),and apnea-hypopnea index(AHI)were measured.Based on ESS scores,T2DM patients were divided into simple T2DM group(ESS score<9,n=99)and EDS group(ESS score≥9,n=33)according to ESS score.The baseline data were compared for each group.Spearman correlation analysis and multivariate logistic regression model were used to evaluate the correlation between HbA1c levels and EDS.The receiver operating characteristic(ROC)curve was used to calculate the area under the curve(AUC)to evaluate the predictive value of HbA1c levels for EDS.Results HbA1c,fasting plasma glucose,AHI index and PSQI score in EDS group were higher than those in T2DM and NC group(P<0.05).Spearman correlation analysis showed that ESS score was positively correlated with HbA1c in T2DM patients(P<0.05).Multivariate logistic regression analysis revealed that elevated HbA1c levels emerged as a significant and independent risk factor for the onset of EDS.The ROC curve indicated that the AUC of HbA1c for predicting EDS was 0.736.Conclusions There is an independent positive correlation between HbA1c levels and EDS in T2DM patients,which provides clues for early identification and treatment of EDS in clinical practice.

Objective To translate Evidence-Informed Decision-Making Competence Measure for Chinese nurses and test its validity and reliability.Methods A research group was set up to use the Brislin translation model to translate the original scale into Chinese,and the back translation,cross-cultural adaptation,pre-experiment and cognitive interview were conducted to finally form the Chinese version of the Evidence-Informed Decision-Making Competence Measure for nurses.A total of 1 247 nurses from 7 tertiary A hospitals in Beijing,Hubei,Hunan and Xinjiang were selected by convenience sampling method in April 2024 to test its reliability and validity.Results 1 026 effective question-naires were collected,with an effective recovery rate of 82.28％.The Chinese version of the Evidence-Informed Decision-Making Competence Measure included 25 items,including knowledge/skill,attitude and behavior.A total of 3 common factors were extracted from exploratory factor analysis,and the cumulative variance contribution rate was 91.725％.The content validity index at the item level was 0.83-1.00;the content validity index at the scale level was 0.988;the calibration association validity was 0.496.The Cronbach's α coefficient of the whole scale was 0.992;the half-point reliability was 0.930;the retest reliability was 0.927.Conclusion The Chinese version of Evidence-Informed Decision-Making Competence Measure for nurses has good reliability and validity,and it can be used to evaluate the evidence-informed decision-making competence of Chinese nurses,provide references for promoting evidence-based nursing practice and evidence-informed decision-making.

Objective To investigate the correlation between hemoglobin A1c(HbA1c)levels and excessive daytime sleepiness(EDS)in patients with type 2 diabetes mellitus(T2DM).Methods A total of 132 T2DM patients and 40 healthy people(NC group)who were treated in the outpatient department of Nanjing Meishan Hospital from December 2020 to December 2022 were selected.General clinical data of the subjects were collected,and their Epworth sleepiness scale(ESS)scores,Pittsburgh sleep quality index(PSQI),and apnea-hypopnea index(AHI)were measured.Based on ESS scores,T2DM patients were divided into simple T2DM group(ESS score<9,n=99)and EDS group(ESS score≥9,n=33)according to ESS score.The baseline data were compared for each group.Spearman correlation analysis and multivariate logistic regression model were used to evaluate the correlation between HbA1c levels and EDS.The receiver operating characteristic(ROC)curve was used to calculate the area under the curve(AUC)to evaluate the predictive value of HbA1c levels for EDS.Results HbA1c,fasting plasma glucose,AHI index and PSQI score in EDS group were higher than those in T2DM and NC group(P<0.05).Spearman correlation analysis showed that ESS score was positively correlated with HbA1c in T2DM patients(P<0.05).Multivariate logistic regression analysis revealed that elevated HbA1c levels emerged as a significant and independent risk factor for the onset of EDS.The ROC curve indicated that the AUC of HbA1c for predicting EDS was 0.736.Conclusions There is an independent positive correlation between HbA1c levels and EDS in T2DM patients,which provides clues for early identification and treatment of EDS in clinical practice.

Objective:To find out whether the performance of a China-made high performance human centrifuge can satisfy the need of high G training by conducting physiological experiments.Methods:The dynamic physical performance of the anti-G equipment with the human centrifuge was tested before 5 subjects underwent the gradual-onset rate (GOR) run and rapid onset rate (ROR) run experiments. The G onset rate of GOR was 0.1 G/s. The relaxed G-tolerance under GOR (GOR tolerance 1) and the anti-G straining maneuver aided G-tolerance under GOR (GOR tolerance 2) were tested respectively. The G onset rate of ROR was 3 G/s, and the closed-loop mode and pre-programed mode were employed respectively. The closed-loop mode involved 5 G 10 s and 8 G 10 s, where the subjects were required to manipulate the joystick to ensure that the real-time curve of the load matched the target curve. In the pre-programmed mode, the subjects were exposed to 8 G 10 s passively, without any operation requirements. A subjective evaluation form was filled out by subjects after the experiments, in which the 14 indexes for evaluation were about the gondola facilities and environment, running processes, medical monitoring and overall assessment.Results:Both the oxygen mask and anti-G suit achieved full pressurization within 2.0 s. The GOR tolerance 1 was [4.0(3.8, 4.6)] G while the GOR tolerance 2 was (6.2±0.5) G, suggesting a statistically significant difference ( Z=-2.63, P=0.008). The HP anti-G straining maneuver effect was (2.0±0.6) G. All the 5 subjects finished the 5 G 10 s experiment in a closed-loop mode. Three of them attempted 8 G 10 s in the closed-loop mode (1 subject achieved only 7.6 G peak acceleration, and the other 2 achieved full 8 G 10 s exposure), while the remaining 2 completed the 8 G 10 s in the pre-programmed mode. In the closed-loop mode, it was found that the stick force was too strong, the guiding G and real time G curve were not easy to distinguish for some of the subjects because the curve colors were similar, and that the subjects could not see the G curves clearly in case of a grayout. Both seat comfort and the voice quality of communication got the highest subjective assessment score [5.0(4.0, 5.0)] while the sensation of tumble got the lowest score (2.8±0.8). The median or mean scores of other subjective evaluation indexes ranged from 3.0 to 4.6 points. The overall score of subjective assessment was [4.0(3.5, 4.0)] points. Conclusions:The China-made high performance human centrifuge can meet the requirements of 8.0 G high G training, which can be made more effective and comfortable if the strong stick force and feeling of tumble during stop running are overcome.

Protein-protein interactions play an extremely important role in the biochemical functions of cells,and in-depth analysis of protein interactions is the key to understanding cellular life activities.In this study,we systematically mined the interacting proteins of Golgi protein 73(GP73)using classical immunoprecipitation combined with mass spectrometry,and sought to further analyze the molecular func-tion of GP73.Hepatocellular carcinoma cell line HepG2 was selected,and a stable cell line overexpress-ing GP73-3Flag was constructed using lentiviral infection technology.A total of 78 high-confidence GP73 interacting proteins were identified by immunoprecipitation coupled with mass spectrometry.Bioinformat-ics analyses suggested that GP73 interacted with nearly 40 cytosolic proteins and participated in the bio-logical processes of RNA transport,splicing,and translation.Further immunofluorescence and cytosolic protein isolation experiments confirmed the cytosolic localization of GP73 in a variety of tumor cells.Based on the 78 interacting proteins,we further screened protein interaction networks related to mRNA splicing and verified the existence of interactions between GP73 and seven proteins,including HNRN-PH3,SMN1,RBM14,andNCBP1,by co-immunoprecipitation experiments.In addition,minigene spli-cing assay results indicated that GP73 inhibited the splicing efficiency of pre-mRNA by cells.This study contributes to the expansion of knowledge regarding the function of GP73 and aids in elucidating its criti-cal role in cell biology and its potential association with diseases.

BACKGROUND: Biomarkers-based prediction of long-term risk of acute coronary syndrome (ACS) is scarce. We aim to develop a risk score integrating clinical routine information (C) and plasma biomarkers (B) for predicting long-term risk of ACS patients. METHODS: We included 2729 ACS patients from the OCEA (Observation of cardiovascular events in ACS patients). The earlier admitted 1910 patients were enrolled as development cohort; and the subsequently admitted 819 subjects were treated as validation cohort. We investigated 10-year risk of cardiovascular (CV) death, myocardial infarction (MI) and all cause death in these patients. Potential variables contributing to risk of clinical events were assessed using Cox regression models and a score was derived using main part of these variables. RESULTS: During 16,110 person-years of follow-up, there were 238 CV death/MI in the development cohort. The 7 most important predictors including in the final model were NT-proBNP, D-dimer, GDF-15, peripheral artery disease (PAD), Fibrinogen, ST-segment elevated MI (STEMI), left ventricular ejection fraction (LVEF), termed as CB-ACS score. C-index of the score for predication of cardiovascular events was 0.79 (95% CI: 0.76-0.82) in development cohort and 0.77 (95% CI: 0.76-0.78) in the validation cohort (5832 person-years of follow-up), which outperformed GRACE 2.0 and ABC-ACS risk score. The CB-ACS score was also well calibrated in development and validation cohort (Greenwood-Nam-D'Agostino: P = 0.70 and P = 0.07, respectively). CONCLUSIONS CB-ACS risk score provides a useful tool for long-term prediction of CV events in patients with ACS. This model outperforms GRACE 2.0 and ABC-ACS ischemic risk score.

As green, sustainable, and environmentally friendly material processing processes using biological cells or enzymes to achieve substance conversion, bioprocesses play an increasingly important role in biomanufacturing. It is difficult to optimize bioprocesses because of the complex relationship at multiple levels and multiple scales. The knowledge of mesoscale behaviors is the key to understanding the dynamics of bioprocesses and to sort out the complex relationships of parameter variations in the spatial-temporal domain. Mesoscale numerical simulation paves a way for understanding these phenomena, and the integration of artificial intelligence (AI) and mesoscale simulation offers new vitality into the optimization of bioprocesses. This article reviews the progress in mesoscale simulation and AI optimization of bioprocesses and discusses the possible development directions, aiming to promote the development of this field.
Artificial Intelligence ; Biotechnology/trends* ; Computer Simulation